1. Field of the Invention
The present invention relates to an image signal encoding apparatus to encode an image signal.
2. Description of the Related Background Art
Hitherto, an adaptive type dynamic range encoding has been known as a method of encoding an image signal highly efficiently (for instance, U.S. Pat. No. 4,703,352). In the adaptive type dynamic range encoding, all of the pixels constructing a picture plane are divided into a plurality of blocks each consisting of a few pixels. For each block the pixels are linearly digitized between the maximum and minimum values of the pixels in that block. The maximum and minimum values of the pixels and, or one of those values the dynamic range value (the difference between the maximum and minimum values), are transmitted together with the digitized values of the pixels.
According to the above encoding method, when the dynamic range in the block is small, the digitizing steps of each pixel become fine. On the contrary, when the dynamic range is large, the digitizing step becomes rough. Therefore, the proper digitization according to the characteristics of human vision can be performed. On the other hand, according to the conventional adaptive type dynamic range encoding method, the number of image transmission bits can be remarkably reduced. For instance, when encoding the image data of eight bits on a block unit basis consisting of 3.times.6 pixels, assuming that the number of digitization bits of each pixel in the block is four, the number of bits per block before compressing (encoding) is 144 (=3.times.6.times.8) bits. After the compression, on the other hand, each pixel datum consists of 72 (=3.times.6.times.4) bits and the number of bits of the data of the maximum value and minimum value is 16 (=8.times.2) bits, so that the total number of bits is set to 88 (=72+16) bits and the number of bits can be compressed to about 1/2.
However, according to the conventional adaptive type dynamic range encoding method, in each block, since the inside of the dynamic range is uniformly divided and each pixel value is digitized, no consideration is paid to the distribution of the pixel values. Thus, there is a case where the digitization error of each pixel increases very considerably, depending on the particular image.